Every dollar a digital business earns passes through its network edge. Checkout requests, API calls, session tokens, mobile app traffic, partner integrations: all of it crosses the same boundary before it reaches an application. That boundary has traditionally been budgeted as a security cost. Huskeys is arguing it should be understood as revenue infrastructure.
The Wall Street Journal first reported that the company has closed a $27 million Series A led by Blackstone Innovations Investments, bringing total funding to $35 million after an $8 million seed round.
The Commercial Logic of Getting the Edge Right
Huskeys is building a Network Edge Security Management platform, a category it abbreviates as NESM. The commercial case for that platform rests on a simple observation: decisions made at the edge have direct financial consequences in both directions.
Serving legitimate traffic accurately keeps customers transacting and revenue flowing. Filtering malicious traffic accurately keeps the organization protected. The requirement is to strengthen security while minimizing false positives, maintaining business continuity, and protecting revenue-critical applications. Those goals are usually presented as a trade-off. Huskeys’ position is that better management makes them compatible.
Itai Gafni, CEO and Co-Founder of Huskeys, put the point in commercial terms: “Every business today runs through its network edge - that’s where your customers, your revenue, and your threats all meet, yet for most organizations, that edge works against them instead of for them.”
Why the Financial Case Is Getting Stronger
Two developments are raising the stakes on edge decisions.
The first is the volume of automated traffic that carries commercial value. Autonomous agents are becoming legitimate users of applications, and non-human traffic is expected to account for 70 percent of all web traffic by 2027. As agents book, purchase, compare, and integrate on behalf of customers, a policy that treats automation cautiously by default starts applying to the majority of inbound commerce.
The second is the pace of the adversarial side. Attackers are using AI to discover and exploit vulnerabilities faster than ever before, and developments such as Mythos demonstrate how AI-driven capabilities are accelerating the speed and scale of cyber threats. Faster discovery compresses the time an organization has to respond after a vulnerability becomes public.
Time to Mitigation as a Financial Metric
That compression is why Virtual Patching reads as a business capability rather than a purely technical one. It allows security teams to mitigate vulnerabilities directly at the network edge within minutes, providing protection while a permanent fix is being developed, tested, and deployed in the application code.
The value is in the delta. Application code fixes move at the speed of an engineering release process. Edge mitigation moves at the speed of a policy push. Shortening the exposure window from a release cycle to minutes reduces risk without pulling engineers off roadmap work to expedite an emergency deployment.
Continuous posture assessment, dynamic policy generation, and orchestration round out the capability set, together helping organizations respond to emerging threats faster.
The Efficiency Argument
There is also a straightforward operating expense dimension. Modern organizations secure their applications across an expanding mix of cloud providers, Content Delivery Networks, Web Application Firewalls, and other edge services. Every one of those tools requires configuration, monitoring, and staff who understand it.
Huskeys’ platform operates on top of existing network infrastructure. Rather than replacing existing investments, it connects and orchestrates the modern network edge ecosystem, including CDNs and WAFs, cloud-native security solutions, and network components such as load balancers, VPCs, and security groups.
That framing protects prior spending. A buyer does not have to write off a multi-year CDN commitment or retrain a team on a new WAF to adopt the platform. The purchase is additive, which shortens the internal approval path considerably compared with a replacement proposal.
The patented Unified Data Model is what makes the additive approach work at a technical level. It creates a common layer of understanding across different environments, technologies, and providers, allowing security insights, policies, and actions to move seamlessly across platforms. The model supports multi-cloud and multi-vendor environments and helps organizations maintain consistent security from the Internet Edge all the way to the application.
Who Wrote the Checks
Blackstone Innovations Investments led. The round also included Merlin Ventures, Skinos Ventures, Zscaler Ventures, Okta Ventures, Bright Pixel Capital, and SV Angel. Skinos Ventures was founded by Shlomo Kramer and Yishay Yovel, pioneers of the WAF and SASE categories.
Individual investors include Eran Reshef, inventor of the WAF and the CAPTCHA, along with executives from Palo Alto Networks, Cloudflare, Check Point, AWS, Google, Microsoft, and Intel.
For a company selling on commercial outcomes, the presence of Zscaler Ventures and Okta Ventures is worth noting. Both are strategic arms of businesses that sell into the same buyers. Their participation indicates the platform is read as an expansion of the edge security budget rather than a reallocation of it.
Adam Fletcher, Chief Information Security Officer at Blackstone, described the reasoning behind the lead investment: “The way organizations secure internet-facing applications is fundamentally changing. AI-driven traffic and increasingly fragmented edge environments require a new approach to security management. Huskeys has built a platform designed to operate at enterprise scale while advancing a new category for the modern network edge. We believe the company is well positioned to redefine how organizations manage edge security, and we’re excited to support Huskeys as they continue to develop their product in this important category.”
Customers That Monetize Their Traffic
The reference list maps closely to the revenue argument. Huskeys’ customer base includes TikTok, LEGOLAND, Ro, Blackstone, and Hugging Face.
TikTok monetizes attention at extraordinary volume. LEGOLAND sells tickets and experiences with a direct link between site availability and gate revenue. Ro operates a regulated healthcare business where trust in the transaction is part of the product. Hugging Face serves developers and automated systems that pull models and datasets continuously. Blackstone brings the requirements of a major financial institution and is now also the lead investor.
Across those accounts, Huskeys analyzes more than a trillion web requests and thousands of network configurations every day.
The Category Being Funded
Gafni tied the founding decision to the tools security teams were handed: “We founded Huskeys because security teams are being asked to protect increasingly complex edge environments with legacy tools that were never designed to work together or to address the challenges of the new AI era.” He continued: “As AI transforms both legitimate traffic and cyberattacks, organizations need an intelligence layer that continuously understands what’s happening across the edge and adapts security in real time. Our goal is to make the network finally work for the business, not against it. That’s the category we’re building.”
What Boards Will Want to See
The pitch to a finance function is measurable in principle. Fewer legitimate transactions interrupted. Shorter time from vulnerability disclosure to mitigation. Less engineering time diverted to emergency edge changes. More consistent policy across an estate that grew by accumulation.
Whether those numbers materialize consistently across different architectures is the question the next stage of the company will answer. What is already established is the scale at which the answer will be tested. A trillion requests a day, across customers ranging from a social platform to a theme park operator to an AI model hub, is a broad enough sample to make the results meaningful.